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Kicking off 2026 by fixing one of the most expensive problems in Microsoft 365.

Most organizations are losing millions without realizing it. 68% of professionals waste 1–5+ hours every week battling poor Microsoft 365 search, duplicate documents, and chasing colleagues for links. In a 5,000-employee company, that hidden inefficiency can reach $130M per year.

Join us for a webinar on how to stop this profit leak and get more value from your Microsoft 365 investment.

Todd Blaschka, Senior Executive, Ben White, Product Manager together with our partner Toni Ressaire, Innovation Director at Altuent will walk you through the strategic solution to the root cause of the chaos:

  • Why M365 search fails: inconsistent or missing file information makes it hard to quickly identify the right, current version of a document
  • What actually fixes it: using smarter, more consistent labeling so content is easier to find, trust, and reuse
  • How teams reclaim capacity: less time searching and rework, more time spent on high-value work like process improvement

January 21 \| 11:00 AM EST \| 5:00 PM CET If SharePoint search has ever slowed your team down, this session is worth your time.

Register and bring you questions: https://hubs.la/Q03Yr13n0

The Hidden $130M Tax: Stopping the Search Time Drain in Microsoft 365
Jon Herke – guest , Tobias Macey – host

Summary Many of the events, ideas, and objects that we try to represent through data have a high degree of connectivity in the real world. These connections are best represented and analyzed as graphs to provide efficient and accurate analysis of their relationships. TigerGraph is a leading database that offers a highly scalable and performant native graph engine for powering graph analytics and machine learning. In this episode Jon Herke shares how TigerGraph customers are taking advantage of those capabilities to achieve meaningful discoveries in their fields, the utilities that it provides for modeling and managing your connected data, and some of his own experiences working with the platform before joining the company.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! This episode is brought to you by Acryl Data, the company behind DataHub, the leading developer-friendly data catalog for the modern data stack. Open Source DataHub is running in production at several companies like Peloton, Optum, Udemy, Zynga and others. Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder. Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, dbt models, Airflow jobs, and business intelligence tools, reducing time to detection and resolution from weeks to just minutes. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. Start trusting your data with Monte Carlo today! Visit http://www.dataengineeringpodcast.com/montecarlo?utm_source=rss&utm_medium=rss to learn more. Your host is Tobias Macey and today I’m interviewing Jon Herke about TigerGraph, a distributed native graph database

Interview

Introduction How did you get involved in the area of data management? Can you describe what TigerGraph is and the story behind it? What are some of the core use cases that you are focused on supporting? How has TigerGraph changed over the past 4 years since I spoke with Todd Blaschka at the Open Data Science Conference? How has the ecosystem of graph databases changed in usage and design in recent years? What are some of the persi

AI/ML Airflow Analytics BI CDP Cloud Computing Data Engineering Data Lake Data Management Data Science dbt ETL/ELT Kubernetes Modern Data Stack Monte Carlo PagerDuty SaaS Data Streaming
Todd Blaschka – guest @ TigerGraph , Andy Eschbacher – guest @ Carto , Tobias Macey – host

Summary

The Open Data Science Conference brings together a variety of data professionals each year in Boston. This week’s episode consists of a pair of brief interviews conducted on-site at the conference. First up you’ll hear from Andy Eschbacher of Carto. He dscribes some of the complexities inherent to working with geospatial data, how they are handling it, and some of the interesting use cases that they enable for their customers. Next is Todd Blaschka, COO of TigerGraph. He explains how graph databases differ from relational engines, where graph algorithms are useful, and how TigerGraph is built to alow for fast and scalable operation.

Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to run a bullet-proof data platform. Go to dataengineeringpodcast.com/linode to get a $20 credit and launch a new server in under a minute. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch. Your host is Tobias Macey and last week I attended the Open Data Science Conference in Boston and recorded a few brief interviews on-site. In this second part you will hear from Andy Eschbacher of Carto about the challenges of managing geospatial data, as well as Todd Blaschka of TigerGraph about graph databases and how his company has managed to build a fast and scalable platform for graph storage and traversal.

Interview

Andy Eschbacher From Carto

What are the challenges associated with storing geospatial data? What are some of the common misconceptions that people have about working with geospatial data?

Contact Info

andy-esch on GitHub @MrEPhysics on Twitter Website

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

Carto Geospatial Analysis GeoJSON

Todd Blaschka From TigerGraph

What are graph databases and how do they differ from relational engines? What are some of the common difficulties that people have when deling with graph algorithms? How does data modeling for graph databases differ from relational stores?

Contact Info

LinkedIn @toddblaschka on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

TigerGraph Graph Databases

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast

API Data Engineering Data Management Data Modelling Data Science GitHub
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